| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com> | |
| // | |
| // This Source Code Form is subject to the terms of the Mozilla | |
| // Public License v. 2.0. If a copy of the MPL was not distributed | |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | |
| // SPDX-License-Identifier: MPL-2.0 | |
| #include "main.h" | |
| #include <Eigen/Tensor> | |
| using Eigen::Tensor; | |
| template <int DataLayout> | |
| static void test_simple_striding() { | |
| Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7); | |
| tensor.setRandom(); | |
| array<ptrdiff_t, 4> strides; | |
| strides[0] = 1; | |
| strides[1] = 1; | |
| strides[2] = 1; | |
| strides[3] = 1; | |
| Tensor<float, 4, DataLayout> no_stride; | |
| no_stride = tensor.stride(strides); | |
| VERIFY_IS_EQUAL(no_stride.dimension(0), 2); | |
| VERIFY_IS_EQUAL(no_stride.dimension(1), 3); | |
| VERIFY_IS_EQUAL(no_stride.dimension(2), 5); | |
| VERIFY_IS_EQUAL(no_stride.dimension(3), 7); | |
| for (int i = 0; i < 2; ++i) { | |
| for (int j = 0; j < 3; ++j) { | |
| for (int k = 0; k < 5; ++k) { | |
| for (int l = 0; l < 7; ++l) { | |
| VERIFY_IS_EQUAL(tensor(i, j, k, l), no_stride(i, j, k, l)); | |
| } | |
| } | |
| } | |
| } | |
| strides[0] = 2; | |
| strides[1] = 4; | |
| strides[2] = 2; | |
| strides[3] = 3; | |
| Tensor<float, 4, DataLayout> stride; | |
| stride = tensor.stride(strides); | |
| VERIFY_IS_EQUAL(stride.dimension(0), 1); | |
| VERIFY_IS_EQUAL(stride.dimension(1), 1); | |
| VERIFY_IS_EQUAL(stride.dimension(2), 3); | |
| VERIFY_IS_EQUAL(stride.dimension(3), 3); | |
| for (int i = 0; i < 1; ++i) { | |
| for (int j = 0; j < 1; ++j) { | |
| for (int k = 0; k < 3; ++k) { | |
| for (int l = 0; l < 3; ++l) { | |
| VERIFY_IS_EQUAL(tensor(2 * i, 4 * j, 2 * k, 3 * l), stride(i, j, k, l)); | |
| } | |
| } | |
| } | |
| } | |
| } | |
| template <int DataLayout> | |
| static void test_striding_as_lvalue() { | |
| Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7); | |
| tensor.setRandom(); | |
| array<ptrdiff_t, 4> strides; | |
| strides[0] = 2; | |
| strides[1] = 4; | |
| strides[2] = 2; | |
| strides[3] = 3; | |
| Tensor<float, 4, DataLayout> result(3, 12, 10, 21); | |
| result.stride(strides) = tensor; | |
| for (int i = 0; i < 2; ++i) { | |
| for (int j = 0; j < 3; ++j) { | |
| for (int k = 0; k < 5; ++k) { | |
| for (int l = 0; l < 7; ++l) { | |
| VERIFY_IS_EQUAL(tensor(i, j, k, l), result(2 * i, 4 * j, 2 * k, 3 * l)); | |
| } | |
| } | |
| } | |
| } | |
| array<ptrdiff_t, 4> no_strides; | |
| no_strides[0] = 1; | |
| no_strides[1] = 1; | |
| no_strides[2] = 1; | |
| no_strides[3] = 1; | |
| Tensor<float, 4, DataLayout> result2(3, 12, 10, 21); | |
| result2.stride(strides) = tensor.stride(no_strides); | |
| for (int i = 0; i < 2; ++i) { | |
| for (int j = 0; j < 3; ++j) { | |
| for (int k = 0; k < 5; ++k) { | |
| for (int l = 0; l < 7; ++l) { | |
| VERIFY_IS_EQUAL(tensor(i, j, k, l), result2(2 * i, 4 * j, 2 * k, 3 * l)); | |
| } | |
| } | |
| } | |
| } | |
| } | |
| template <typename T, int DataLayout> | |
| static void test_striding_packet_paths() { | |
| // Sizes with partial-packet tails; expression-sourced reads so the packet | |
| // path is exercised, sweeping strides that keep the inner dimension intact | |
| // (contiguous inner runs), that stride it (gathers), and the identity. | |
| // setRandom() draws integers from the full range of T, so the values scaled | |
| // below would overflow; bounded draws keep them representable for every T. | |
| Tensor<T, 3, DataLayout> tensor(17, 5, 7); | |
| setRandomDataInRange(tensor, T(-10), T(10)); | |
| const ptrdiff_t stride_sets[][3] = {{1, 1, 1}, {2, 1, 1}, {1, 2, 1}, {1, 1, 2}, {2, 2, 2}, {3, 1, 2}}; | |
| for (const auto& s : stride_sets) { | |
| array<ptrdiff_t, 3> strides{{s[0], s[1], s[2]}}; | |
| // Expression-sourced: the argument has no raw buffer, so the striding | |
| // serves packets assembled from the nested expression. | |
| Tensor<T, 3, DataLayout> result = (tensor * tensor.constant(T(2))).stride(strides); | |
| for (Index i = 0; i < result.dimension(0); ++i) { | |
| for (Index j = 0; j < result.dimension(1); ++j) { | |
| for (Index k = 0; k < result.dimension(2); ++k) { | |
| VERIFY_IS_EQUAL(result(i, j, k), T(2) * tensor(i * s[0], j * s[1], k * s[2])); | |
| } | |
| } | |
| } | |
| // Lvalue: writePacket through the strided destination. | |
| Tensor<T, 3, DataLayout> dst(17, 5, 7); | |
| dst.setZero(); | |
| Tensor<T, 3, DataLayout> src((17 + s[0] - 1) / s[0], (5 + s[1] - 1) / s[1], (7 + s[2] - 1) / s[2]); | |
| setRandomDataInRange(src, T(-10), T(10)); | |
| dst.stride(strides) = src * src.constant(T(3)); | |
| for (Index i = 0; i < src.dimension(0); ++i) { | |
| for (Index j = 0; j < src.dimension(1); ++j) { | |
| for (Index k = 0; k < src.dimension(2); ++k) { | |
| VERIFY_IS_EQUAL(dst(i * s[0], j * s[1], k * s[2]), T(3) * src(i, j, k)); | |
| } | |
| } | |
| } | |
| } | |
| } | |
| template <typename T, int DataLayout> | |
| static void test_striding_without_impl_packet_access() { | |
| // A TensorRef argument exposes only coefficient access, but the striding | |
| // still serves packets by assembling them coefficient by coefficient. | |
| Tensor<T, 3, DataLayout> tensor(17, 5, 7); | |
| tensor.setRandom(); | |
| const Eigen::TensorRef<const Tensor<T, 3, DataLayout>> ref(tensor); | |
| array<ptrdiff_t, 3> identity{{1, 1, 1}}; | |
| // Pin the capabilities this test relies on: the nested TensorRef evaluator | |
| // must not have packet access (otherwise this test exercises nothing), while | |
| // the striding evaluator on top of it must still advertise it. | |
| typedef Eigen::TensorRef<const Tensor<T, 3, DataLayout>> RefType; | |
| typedef decltype(std::declval<const RefType&>().stride(identity)) StrideExprType; | |
| typedef Eigen::TensorEvaluator<const RefType, Eigen::DefaultDevice> RefEvaluator; | |
| typedef Eigen::TensorEvaluator<const StrideExprType, Eigen::DefaultDevice> StrideEvaluator; | |
| EIGEN_STATIC_ASSERT(!RefEvaluator::PacketAccess, YOU_MADE_A_PROGRAMMING_MISTAKE) | |
| EIGEN_STATIC_ASSERT(StrideEvaluator::PacketAccess, YOU_MADE_A_PROGRAMMING_MISTAKE) | |
| Tensor<T, 3, DataLayout> result = ref.stride(identity); | |
| for (Index i = 0; i < result.size(); ++i) { | |
| VERIFY_IS_EQUAL(result.coeff(i), tensor.coeff(i)); | |
| } | |
| array<ptrdiff_t, 3> strides{{2, 1, 3}}; | |
| Tensor<T, 3, DataLayout> strided = ref.stride(strides); | |
| for (Index i = 0; i < strided.dimension(0); ++i) { | |
| for (Index j = 0; j < strided.dimension(1); ++j) { | |
| for (Index k = 0; k < strided.dimension(2); ++k) { | |
| VERIFY_IS_EQUAL(strided(i, j, k), tensor(i * 2, j, k * 3)); | |
| } | |
| } | |
| } | |
| } | |
| EIGEN_DECLARE_TEST(tensor_striding) { | |
| CALL_SUBTEST(test_simple_striding<ColMajor>()); | |
| CALL_SUBTEST(test_simple_striding<RowMajor>()); | |
| CALL_SUBTEST(test_striding_as_lvalue<ColMajor>()); | |
| CALL_SUBTEST(test_striding_as_lvalue<RowMajor>()); | |
| CALL_SUBTEST((test_striding_packet_paths<float, ColMajor>())); | |
| CALL_SUBTEST((test_striding_packet_paths<float, RowMajor>())); | |
| CALL_SUBTEST((test_striding_packet_paths<int, ColMajor>())); | |
| CALL_SUBTEST((test_striding_packet_paths<int, RowMajor>())); | |
| CALL_SUBTEST((test_striding_without_impl_packet_access<float, ColMajor>())); | |
| CALL_SUBTEST((test_striding_without_impl_packet_access<float, RowMajor>())); | |
| } |